Overview

Modern backend systems demand more than clean code and working endpoints. They demand predictable performance, strong security boundaries, observability by default, and the ability to survive real-world failure. FastAPI in Production is written for engineers who already know FastAPI-and now need to operate it confidently at scale. This book is not an introduction. It is a production playbook. You will learn how to design FastAPI as a control plane for modern systems: AI backends, cloud-native APIs, data platforms, and high-throughput services. Every chapter is hands-on, infrastructure-aware, and grounded in operational reality. The focus is not on features, but on behavior under load, failure, and change. You will build production-ready FastAPI systems that: Scale predictably with async execution and controlled concurrency Enforce strict API contracts using Pydantic v2 and versioned schemas Manage databases, connection pools, and transactions safely at scale Serve AI inference, embeddings, and streaming responses with hard budgets Isolate durable background work from request paths Apply real authentication, authorization, rate limiting, and abuse prevention Expose meaningful logs, metrics, and traces with OpenTelemetry Deploy immutably using containers and promote safely across environments Survive load spikes, dependency failures, restarts, and bad deployments A full end-to-end capstone project guides you through building, securing, observing, load-testing, and deploying a complete FastAPI-based AI API platform-the same way it would be done by a mature production team. You will not only make the system work; you will prove it works through load tests, failure drills, and production readiness checklists. The appendices provide operator-grade references you will return to long after reading: Production command and configuration cheat sheets Performance and load-testing toolkits Security and hardening checklists Troubleshooting and failure runbooks A 2026-ready roadmap for scaling FastAPI and AI systems This book is written for: Backend and platform engineers running FastAPI in production AI engineers building inference and RAG APIs DevOps and SREs responsible for reliability and scale Technical leads designing long-lived API platforms If you want to understand why FastAPI behaves the way it does under pressure-and how to design systems that remain stable when everything goes wrong-this book is for you. Build less guesswork. Ship with confidence. Operate FastAPI like a production system.

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